Braintrust vs. LangChain

Braintrust and LangChain are two widely used platforms in AI development, each catering to different needs. Braintrust specializes in LLM evaluation, providing tools to assess and optimize AI models, while LangChain is designed for building modular AI applications by linking different components together. While both offer valuable capabilities, they also come with limitations that may require additional integrations to create a fully functional AI development pipeline.

For teams seeking a more complete solution, there is another option worth considering. Sandgarden combines the strengths of both Braintrust and LangChain while addressing their weaknesses, providing a more scalable and efficient AI development environment. In this comparison, we’ll analyze how Braintrust and LangChain compare while also exploring how an alternative like Sandgarden can deliver a more robust and streamlined approach.

Braintrust’s model assessment tools versus LangChain’s modular AI development framework.

Feature Comparison

Prompt Management

LLM Evaluation

Version Control

Analytics

Tracing

Metrics

Logging

API First

Self-Hosted

On-Prem Deployment

Dedicated Infrastructure

Access Control

SSO

Data Encryption

Braintrust

Braintrust offers an LLM evaluation suite, providing tools for testing and optimizing model performance over time. With a focus on experimentation and a user-friendly testing library, users can quantify results against AI initiatives.

At the core of Braintrust is a software development kit (SDK) that integrates into existing infrastructure and CI/CD pipelines. This enables continuous evaluations that offer insights into LLM accuracy and reliability. As a third-party evaluator Braintrust is model agnostic, allowing it to work across multiple systems and platforms.

That said, Braintrust is not without its drawbacks:

Limited ability to move workloads to production
Limited scalability for large-scale operations
Unwieldy for less technical users

View more Braintrust alternatives

LangChain

LangChain provides a framework that enables developers to build applications with interoperable components, offering control over AI-driven workflows. With LangChain, a company can create context-aware applications that integrate with company data and APIs.

At the core of LangChain is its ability to integrate with various components. LangGraph is a framework designed to build controllable, agent-driven workflows. LangChain’s infrastructure also supports scalable deployment with LangGraph Cloud, which offers built-in persistence and distributed task queues. LangSmith, another component, provides tools for debugging, testing, and monitoring LLM applications.

That said, LangChain is not without its drawbacks:

Slow to adapt to new models and functionalities
Steep learning curve for unique abstractions
Limited deployment options

View more LangChain alternatives

Sandgarden

Sandgarden provides production-ready infrastructure by automatically crafting the pipeline of tools and processes needed to experiment with AI. This helps businesses move from test to production without figuring out how to deploy, monitor, and scale the stack.

With Sandgarden you get an enterprise AI runtime engine that lets you stand up a test, refine and iterate, all in support of determining how to accelerate your business processes quickly. Time to value is their ethos and as such the platform is freely available to try without going through a sales process.

Conclusion

Braintrust and LangChain are both widely used in AI development, but each has significant limitations. Braintrust is focused on LLM evaluation, helping teams assess AI model performance, but it lacks the infrastructure, security, and advanced analytics required for a fully integrated workflow. LangChain, meanwhile, is popular for its modular AI framework, allowing developers to build complex applications, but it requires significant customization and additional tools for version control, logging, and enterprise-grade security. Neither solution provides an all-in-one environment for AI teams to efficiently manage the entire development lifecycle.

Sandgarden surpasses both by offering a comprehensive, high-performance AI development platform. Unlike Braintrust and LangChain, Sandgarden includes built-in prompt management, real-time analytics, and end-to-end security, ensuring that teams can develop, test, and deploy models without external dependencies. Its API-first design, combined with flexible deployment options and full encryption, makes it the best choice for organizations that demand both innovation and reliability. For teams looking to streamline their AI workflows while maintaining top-tier security and scalability, Sandgarden is the clear winner.